Update app.py

app.py

@@ -1,18 +1,11 @@
 import streamlit as st
 import requests
-
-# Hugging Face Inference API endpoint
-API_URL = "https://api-inference.huggingface.co/models/microsoft/DialoGPT-medium"
-headers = {"Authorization": "Bearer Component_Chatbot"}
-
-def query_chatbot(prompt):
-    payload = {"inputs": prompt}
-    response = requests.post(API_URL, headers=headers, json=payload)
-    return response.json()[0]['generated_text']
+from scraping_utils import scrape_farnell, scrape_digikey
+from urllib.parse import quote
 
 # Streamlit app
 st.title("Electronics Component Chatbot")
-st.write("Ask me anything about electronics components!")
+st.write("Search for electronics components from Farnell and Digi-Key!")
 
 # Initialize chat history
 if "messages" not in st.session_state:
@@ -24,16 +17,33 @@ for message in st.session_state.messages:
         st.markdown(message["content"])
 
 # Accept user input
-if prompt := st.chat_input("What is your question?"):
+if prompt := st.chat_input("What component are you looking for?"):
     # Add user message to chat history
     st.session_state.messages.append({"role": "user", "content": prompt})
     with st.chat_message("user"):
         st.markdown(prompt)
 
-    # Get chatbot response
-    response = query_chatbot(prompt)
-    
+    # Scrape component data
+    try:
+        farnell_results = scrape_farnell(quote(prompt))
+        digikey_results = scrape_digikey(quote(prompt))
+
+        # Format response
+        response = "### Farnell Results:\n"
+        for component in farnell_results[:3]:
+            response += f"- **{component['name']}**: {component['description']} ([Datasheet]({component['datasheet_link']}))\n"
+        
+        response += "\n### Digi-Key Results:\n"
+        for component in digikey_results[:3]:
+            response += f"- **{component['name']}**: {component['description']} ([Datasheet]({component['datasheet_link']}))\n"
+
+        if not farnell_results and not digikey_results:
+            response = "Sorry, no results found for your query."
+
+    except Exception as e:
+        response = f"An error occurred: {str(e)}"
+
     # Add chatbot response to chat history
     st.session_state.messages.append({"role": "assistant", "content": response})
     with st.chat_message("assistant"):
-        st.markdown(response)
+        st.markdown(response)